The snowslide python package was written by Guillem Carcanade, intern in the glaciology team of IGE Grenoble based on the algorithms described by Bernhardt & Schulz, 2010 and Gruber, 2007.
This package provides a simple parametrisation of the transport and deposition of snow in mountain terrains. It has been designed for applications in glaciological modeling, and specifically to be used through the OGGM workflow. While the package provides methods for use in conjunction with OGGM, the basic functions can also be called up and used independently. Snowslide can then work in a wide variety of context that includes gravitational transport. Snowslide operates the estimated redistribution of snow by avalanches using only two inputs :
- a dem given as a path to a .tif file
- information about initial snow depths
The next steps goes into more details about how snowslide works and should be used.
Snowslide relies on basic python librairies for data manipulation. Nonetheless, the routing of the snow is calculated by an external python module called pysheds (docs : https://github.com/mdbartos/pysheds/). Running snowslide therefore requires installing pysheds (pip install pysheds).
The list of all snowslide dependancies is given as follow :
- pysheds
- rasterio
- numpy
- xarray
- pandas
- matplotlib
- os
- datetime
These libraries must be installed to run snowslide. Then you can install snowslide using pip :
$ pip install -e git+https://github.com/GuillemCF/Snowslide.git
This should clone the snowslide GitHub repository and install it as a python package in the active virtual environment chosen.
.gitignore: for git users onlyLICENSE.txt: (https://help.github.com/articles/licensing-a-epository/) license of the codeREADME.md: this pagepyproject.toml: this is what makes your package insallable bypip. It contains a set of simple instructions regarding e.g. the name of the package, its version number, or where to find command line scripts.
__init__.py: tells python that the directory is a package and enables the "dotted module names" import syntax. It is often empty,fla but here we added some entry points to the package's API and the version string.snowslide_main.py: main module that operates the simulationfunctions.py: various functions used in the main module and defined separatlydisplay_2Dresults.py: very basic display functionalities ofered to the userdisplay_3Dresults.py: very basic display functionalities ofered to the user (Disabled for now)oggm_snowslide_compat.py: module recognised as a task by OGGM and used to launch snowslide through a workflow using OGGM. This allows snowslide to use all the possibilities offered by OGGM.
(see after)
test_snowslide.py: is a module that can be detected by pytest. It includes various functions
that test the expected behaviour of snowslide algorithm.
./data : contains basic data to run the tests
Through a main function defined in snowslide_main, snowslide uses a number of functions which are
present in the functions.py file. These are the following :
- dem_flow() : This function can preprocess the dem (or not) and compute the flow direction based on the total elevation surface (dem + snow depth)
- precipitations_base() : This function initialize an ideal SND matrix based on solid precipitation information
- slope() : This function calculate a slope matrix based on the dem matrix
- snow_routing() : That function routes the snow based on the routing method chosen ('mfd' or 'd8'). It is called at each iteration.
- SND_max_exponential(): Function that compute the maximal height of snow each pixel can store based on the slope. The function is an exponential and parameters are estimated from 'Bernhardt & Schulz 2007'.
- reframe_tif() : To quickly crop a DEM, retaining only the area of interest. It displays the initial DEM, and the user can then enter the x and y windows of the zone to be retained so that the function can store a new DEM entitled: 'reframed_dem'.
- resampling_dem() : This function allows to resample a dem to another resolution. It can be used to increase the speed of calculations if high resolution is not required.
The display_2Dresults.py and display_3Dresults.py are used in snowslide_complete() function defined in
snowslide_main.py. This function offers the same simulation as snowslide_base(), but simply provides functions
for recording and displaying output that can simplify the use of snowslide for the user in certain cases. We don't
use it at the moment, so we recommend that users use the snowslide_base() function instead. The rest of the readme
gives an example of using snowslide first in a snowslide workflow and then in an OGGM workflow.
To make it easier for users to use the package, we have produced a series of tutorial notebooks that explain how to use snowslide, its principles and its performance. These notebooks fall into 3 categories:
To understand how to use snowslide in a classic workflow, see the notebook in https://github.com/GuillemCF/Snowslide/blob/main/example/How_to_use_snowslide.ipynb To understand how to use snowslide in a OGGM workflow, see the notebook in https://github.com/GuillemCF/Snowslide/blob/main/example/How_to_use_OGGMxSnowslide.ipynb To understand how to use snowslide output from the OGGM workflow, see the notebook in https://github.com/OGGM/Snowslide/blob/main/example/How_to_use_OGGMxSnowslidePrePro.ipynb To get to grips with the preprocessing functions associated with the algorithm, see the notebook ...
To understand how snow heights can be initialized in the model, see the notebook: ... To understand how snow is routed and how convergence is ensured, see the notebook: ...
To see the results of the algorithm under idealized conditions, see the notebook: ... To see the results of the algorithm in real-life conditions, see the notebook: ... To see the results of the algorithm applied globally coupled with OGGM, see the notebook: ... To analyse the algorithm's computational performance, see the notebook: ... To understand the limit cases for using the algorithm, see the notebook: ...